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            <h2 class="title" style="clear: both"><a id="transapp_tune"></a>Transaction tuning</h2>
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      <p>There are a few different issues to consider when tuning the performance
of Berkeley DB transactional applications.  First, you should review
<a class="xref" href="am_misc_tune.html" title="Access method tuning">Access method tuning</a>, as the
tuning issues for access method applications are applicable to
transactional applications as well.  The following are additional tuning
issues for Berkeley DB transactional applications:</p>
      <div class="variablelist">
        <dl>
          <dt>
            <span class="term">access method</span>
          </dt>
          <dd>Highly concurrent applications should use the Queue access method, where
possible, as it provides finer-granularity of locking than the other
access methods.  Otherwise, applications usually see better concurrency
when using the Btree access method than when using either the Hash or
Recno access methods.</dd>
          <dt>
            <span class="term">record numbers</span>
          </dt>
          <dd>Using record numbers outside of the Queue access method will often slow
down concurrent applications as they limit the degree of concurrency
available in the database.  Using the Recno access method, or the Btree
access method with retrieval by record number configured can slow
applications down.</dd>
          <dt>
            <span class="term">Btree database size</span>
          </dt>
          <dd>When using the Btree access method, applications supporting concurrent
access may see excessive numbers of deadlocks in small databases.  There
are two different approaches to resolving this problem.  First, as the
Btree access method uses page-level locking, decreasing the database
page size can result in fewer lock conflicts.  Second, in the case of
databases that are cyclically growing and shrinking, turning off reverse
splits (with <a href="../api_reference/C/dbset_flags.html#dbset_flags_DB_REVSPLITOFF" class="olink">DB_REVSPLITOFF</a>) can leave the database with enough
pages that there will be fewer lock conflicts.</dd>
          <dt>
            <span class="term">read locks</span>
          </dt>
          <dd>Performing all read operations outside of transactions or at
<a class="xref" href="transapp_read.html" title="Degrees of isolation">Degrees of isolation</a> can often
significantly increase application throughput.  In addition, limiting
the lifetime of non-transactional cursors will reduce the length of
times locks are held, thereby improving concurrency.</dd>
          <dt>
            <span class="term"><a href="../api_reference/C/envset_flags.html#set_flags_DB_DIRECT_DB" class="olink">DB_DIRECT_DB</a>, <a href="../api_reference/C/envlog_get_config.html#log_set_config_DB_LOG_DIRECT" class="olink">DB_LOG_DIRECT</a></span>
          </dt>
          <dd>
On some systems, avoiding caching in the operating system can improve
write throughput and allow the creation of larger Berkeley DB caches.</dd>
          <dt>
            <span class="term"><a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a>, <a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a></span>
          </dt>
          <dd>
            <p>
            Consider decreasing the level of isolation of transaction using
            the <a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a>, or <a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a> flags for
            transactions or cursors or the <a href="../api_reference/C/dbopen.html#dbopen_DB_READ_UNCOMMITTED" class="olink">DB_READ_UNCOMMITTED</a> flag on
            individual read operations.  The <a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a> flag will
            release read locks on cursors as soon as the data page is
            nolonger referenced.  This is also called 
            <span class="emphasis"><em> degree 2 isolation</em></span>.  This will
            tend to block write operations for shorter periods for
            applications that do not need to have repeatable reads for
            cursor operations.
        </p>
            <p>
            The <a href="../api_reference/C/dbcget.html#dbcget_DB_READ_COMMITTED" class="olink">DB_READ_COMMITTED</a> flag will allow read operations to
            potentially return data which has been modified but not yet
            committed, and can significantly increase application
            throughput in applications that do not require data be
            guaranteed to be permanent in the database.  This is also
            called <span class="emphasis"><em>degree 1 isolation</em></span>,
            or <span class="emphasis"><em>dirty reads</em></span>.
        </p>
          </dd>
          <dt>
            <span class="term">
              <a href="../api_reference/C/dbcget.html#dbcget_DB_RMW" class="olink">DB_RMW</a>
            </span>
          </dt>
          <dd> If there are many deadlocks, consider
using the <a href="../api_reference/C/dbcget.html#dbcget_DB_RMW" class="olink">DB_RMW</a> flag to
immediately acquire write locks when reading data items that will
subsequently be modified.  Although this flag may increase contention
(because write locks are held longer than they would otherwise be), it
may decrease the number of deadlocks that occur.</dd>
          <dt>
            <span class="term"><a href="../api_reference/C/envset_flags.html#set_flags_DB_TXN_WRITE_NOSYNC" class="olink">DB_TXN_WRITE_NOSYNC</a>, <a href="../api_reference/C/envset_flags.html#envset_flags_DB_TXN_NOSYNC" class="olink">DB_TXN_NOSYNC</a></span>
          </dt>
          <dd>By default, transactional commit in Berkeley DB implies durability, that is,
all committed operations will be present in the database after recovery
from any application or system failure.  For applications not requiring
that level of certainty, specifying the <a href="../api_reference/C/envset_flags.html#envset_flags_DB_TXN_NOSYNC" class="olink">DB_TXN_NOSYNC</a> flag will
often provide a significant performance improvement. In this case, the
database will still be fully recoverable, but some number of committed
transactions might be lost after application or system failure.</dd>
          <dt>
            <span class="term">access databases in order</span>
          </dt>
          <dd>When modifying multiple databases in a single transaction, always access
physical files and databases within physical files, in the same order
where possible.  In addition, avoid returning to a physical file or
database, that is, avoid accessing a database, moving on to another
database and then returning to the first database.  This can
significantly reduce the chance of deadlock between threads of
control.</dd>
          <dt>
            <span class="term">large key/data items</span>
          </dt>
          <dd>Transactional protections in Berkeley DB are guaranteed by before and after
physical image logging.  This means applications modifying large
key/data items also write large log records, and, in the case of the
default transaction commit, threads of control must wait until those
log records have been flushed to disk.  Applications supporting
concurrent access should try and keep key/data items small wherever
possible.</dd>
          <dt>
            <span class="term">mutex selection</span>
          </dt>
          <dd>
            <p>
        During configuration, Berkeley DB selects a mutex implementation
        for the architecture. Berkeley DB normally prefers blocking-mutex
        implementations over non-blocking ones.  For example, Berkeley DB
        will select POSIX pthread mutex interfaces rather than
        assembly-code test-and-set spin mutexes because pthread mutexes are
        usually more efficient and less likely to waste CPU cycles spinning
        without getting any work accomplished.
    </p>
            <p>
        For some applications and systems (generally highly concurrent
        applications on large multiprocessor systems), Berkeley DB makes
        the wrong choice.  In some cases, better performance can be
        achieved by configuring with the <a class="link" href="build_unix_conf.html#build_unix_conf.--with-mutex">--with-mutex</a>
        argument and selecting a different mutex implementation than the
        one selected by Berkeley DB.  When a test-and-set spin mutex
        implementation is selected, it may be useful to tune the number of
        spins made before yielding the processor and sleeping.  For more
        information, see the <a href="../api_reference/C/mutexset_tas_spins.html" class="olink">DB_ENV-&gt;mutex_set_tas_spins()</a> method.
    </p>
            <p>
        Finally, Berkeley DB may put multiple mutexes on individual cache
        lines.  When tuning Berkeley DB for large multiprocessor systems,
        it may be useful to tune mutex alignment using the <a href="../api_reference/C/mutexset_align.html" class="olink">DB_ENV-&gt;mutex_set_align()</a>
        method.
    </p>
          </dd>
          <dt>
            <span class="term">
              <a class="link" href="build_unix_conf.html#build_unix_conf.--enable-posixmutexes">--enable-posixmutexes</a>
            </span>
          </dt>
          <dd>By default, the Berkeley DB library will only select the POSIX pthread mutex
implementation if it supports mutexes shared between multiple processes.
If your application does not share its database environment between
processes and your system's POSIX mutex support was not selected because
it did not support inter-process mutexes, you may be able to increase
performance and transactional throughput by configuring with the
<a class="link" href="build_unix_conf.html#build_unix_conf.--enable-posixmutexes">--enable-posixmutexes</a> argument.</dd>
          <dt>
            <span class="term">log buffer size</span>
          </dt>
          <dd>Berkeley DB internally maintains a buffer of log writes.   The buffer is
written to disk at transaction commit, by default, or, whenever it
is filled.  If it is consistently being filled before transaction
commit, it will be written multiple times per transaction, costing
application performance.  In these cases, increasing the size of the
log buffer can increase application throughput.</dd>
          <dt>
            <span class="term">log file location</span>
          </dt>
          <dd>If the database environment's log files are on the same disk as the
databases, the disk arms will have to seek back-and-forth between the
two.  Placing the log files and the databases on different disk arms
can often increase application throughput.</dd>
          <dt>
            <span class="term">trickle write</span>
          </dt>
          <dd>In some applications, the cache is sufficiently active and dirty that
readers frequently need to write a dirty page in order to have space in
which to read a new page from the backing database file.  You can use
the <a href="../api_reference/C/db_stat.html" class="olink">db_stat utility</a> (or the statistics returned by the
<a href="../api_reference/C/mempstat.html" class="olink">DB_ENV-&gt;memp_stat()</a> method) to see how often this is happening in your
application's cache.  In this case, using a separate thread of control
and the <a href="../api_reference/C/memptrickle.html" class="olink">DB_ENV-&gt;memp_trickle()</a> method to trickle-write pages can often increase
the overall throughput of the application.</dd>
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